CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
Cancelable Biometric Filters for Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
A secure biometric authentication scheme based on robust hashing
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy extractors for continuous distributions
ASIACCS '07 Proceedings of the 2nd ACM symposium on Information, computer and communications security
Generating Cancelable Fingerprint Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
EURASIP Journal on Advances in Signal Processing
Fingerprint hardening with randomly selected chaff minutiae
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Protecting Biometric Templates With Sketch: Theory and Practice
IEEE Transactions on Information Forensics and Security - Part 2
Template-Free Biometric-Key Generation by Means of Fuzzy Genetic Clustering
IEEE Transactions on Information Forensics and Security
A New Method for Generating an Invariant Iris Private Key Based on the Fuzzy Vault System
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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The recent biometric template protection methods often propose salting or one-way transformation functions and biometric cryptosystems which are capable of key binding or key generation to provide the revocability of the templates. Moreover, the use of multiple instances of a biometric trait proposes more robust features which are then combined with the well-known template protection methods. In this study, a normal densities based linear classifier is proposed to distinguish the features associated with each user and cluster them to generate an identity code by mapping the center of the cluster to a N-dimensional quantized bin. The resulting code is converted to a bit stream by a hashing mechanism to let user revoke his biometric in case of key compromise. This method presents the advantage of representing an individual by using his plenty of features instead of a single one in a supervised manner.